{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# *Future Frame Prediction for Anomaly Detection – A New Baseline*\n",
    "\n",
    "### Test the pre-trained model on several datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "usage: ipykernel_launcher.py [-h] [-g GPU] [-i ITERS] [-b BATCH]\n",
      "                             [--num_his NUM_HIS] [-d DATASET]\n",
      "                             [--train_folder TRAIN_FOLDER]\n",
      "                             [--test_folder TEST_FOLDER] [--config CONFIG]\n",
      "                             [--snapshot_dir SNAPSHOT_DIR]\n",
      "                             [--summary_dir SUMMARY_DIR] [--psnr_dir PSNR_DIR]\n",
      "                             [--evaluate EVALUATE]\n",
      "ipykernel_launcher.py: error: unrecognized arguments: -f /run/user/1004/jupyter/kernel-ce2f9280-548d-416c-bf91-977db3850625.json\n"
     ]
    },
    {
     "ename": "SystemExit",
     "evalue": "2",
     "output_type": "error",
     "traceback": [
      "An exception has occurred, use %tb to see the full traceback.\n",
      "\u001b[0;31mSystemExit\u001b[0m\u001b[0;31m:\u001b[0m 2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/brianyao/Envs/tf/lib/python3.6/site-packages/IPython/core/interactiveshell.py:3275: UserWarning: To exit: use 'exit', 'quit', or Ctrl-D.\n",
      "  warn(\"To exit: use 'exit', 'quit', or Ctrl-D.\", stacklevel=1)\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "import os\n",
    "import time\n",
    "import numpy as np\n",
    "import pickle\n",
    "\n",
    "\n",
    "from models import generator\n",
    "from utils import DataLoader, load, save, psnr_error\n",
    "from constant import const\n",
    "import evaluate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "slim = tf.contrib.slim\n",
    "\n",
    "os.environ['CUDA_DEVICES_ORDER'] = \"PCI_BUS_ID\"\n",
    "os.environ['CUDA_VISIBLE_DEVICES'] = const.GPU\n",
    "\n",
    "dataset_name = const.DATASET\n",
    "test_folder = const.TEST_FOLDER\n",
    "\n",
    "num_his = const.NUM_HIS\n",
    "height, width = 256, 256\n",
    "\n",
    "snapshot_dir = const.SNAPSHOT_DIR\n",
    "psnr_dir = const.PSNR_DIR\n",
    "evaluate_name = const.EVALUATE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test inputs = Tensor(\"dataset/strided_slice:0\", shape=(1, 256, 256, 12), dtype=float32)\n",
      "test prediction gt = Tensor(\"dataset/strided_slice_1:0\", shape=(1, 256, 256, 3), dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "# define dataset\n",
    "with tf.name_scope('dataset'):\n",
    "    test_video_clips_tensor = tf.placeholder(shape=[1, height, width, 3 * (num_his + 1)],\n",
    "                                             dtype=tf.float32)\n",
    "    test_inputs = test_video_clips_tensor[..., 0:num_his*3]\n",
    "    test_gt = test_video_clips_tensor[..., -3:]\n",
    "    print('test inputs = {}'.format(test_inputs))\n",
    "    print('test prediction gt = {}'.format(test_gt))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "testing = generator\n",
      "Init global successfully!\n"
     ]
    }
   ],
   "source": [
    "# define testing generator function and\n",
    "# in testing, only generator networks, there is no discriminator networks and flownet.\n",
    "with tf.variable_scope('generator', reuse=None):\n",
    "    print('testing = {}'.format(tf.get_variable_scope().name))\n",
    "    test_outputs = generator(test_inputs, layers=4, output_channel=3)\n",
    "    test_psnr_error = psnr_error(gen_frames=test_outputs, gt_frames=test_gt)\n",
    "\n",
    "\n",
    "config = tf.ConfigProto()\n",
    "config.gpu_options.allow_growth = True\n",
    "with tf.Session(config=config) as sess:\n",
    "    # dataset\n",
    "    data_loader = DataLoader(test_folder, height, width)\n",
    "\n",
    "    # initialize weights\n",
    "    sess.run(tf.global_variables_initializer())\n",
    "    print('Init global successfully!')\n",
    "\n",
    "    # tf saver\n",
    "    saver = tf.train.Saver(var_list=tf.global_variables(), max_to_keep=None)\n",
    "\n",
    "    restore_var = [v for v in tf.global_variables()]\n",
    "    loader = tf.train.Saver(var_list=restore_var)\n",
    "\n",
    "    def inference_func(ckpt, dataset_name, evaluate_name):\n",
    "        load(loader, sess, ckpt)\n",
    "        \n",
    "        psnr_records = []\n",
    "        videos_info = data_loader.videos\n",
    "        num_videos = len(videos_info.keys())\n",
    "        total = 0\n",
    "        timestamp = time.time()\n",
    "\n",
    "        for video_name, video in videos_info.items():\n",
    "            length = video['length']\n",
    "            total += length\n",
    "            psnrs = np.empty(shape=(length,), dtype=np.float32)\n",
    "\n",
    "            for i in range(num_his, length):\n",
    "                video_clip = data_loader.get_video_clips(video_name, i - num_his, i + 1)\n",
    "                psnr = sess.run(test_psnr_error,\n",
    "                                feed_dict={test_video_clips_tensor: video_clip[np.newaxis, ...]})\n",
    "                psnrs[i] = psnr\n",
    "\n",
    "                print('video = {} / {}, i = {} / {}, psnr = {:.6f}'.format(\n",
    "                    video_name, num_videos, i, length, psnr))\n",
    "\n",
    "            psnrs[0:num_his] = psnrs[num_his]\n",
    "            psnr_records.append(psnrs)\n",
    "\n",
    "        result_dict = {'dataset': dataset_name, 'psnr': psnr_records, 'flow': [], 'names': [], 'diff_mask': []}\n",
    "\n",
    "        used_time = time.time() - timestamp\n",
    "        print('total time = {}, fps = {}'.format(used_time, total / used_time))\n",
    "\n",
    "        # TODO specify what's the actual name of ckpt.\n",
    "        pickle_path = os.path.join(psnr_dir, os.path.split(ckpt)[-1])\n",
    "        with open(pickle_path, 'wb') as writer:\n",
    "            pickle.dump(result_dict, writer, pickle.HIGHEST_PROTOCOL)\n",
    "\n",
    "        results = evaluate.evaluate(evaluate_name, pickle_path)\n",
    "        print(results)\n",
    "\n",
    "\n",
    "    if os.path.isdir(snapshot_dir):\n",
    "        def check_ckpt_valid(ckpt_name):\n",
    "            is_valid = False\n",
    "            ckpt = ''\n",
    "            if ckpt_name.startswith('model.ckpt-'):\n",
    "                ckpt_name_splits = ckpt_name.split('.')\n",
    "                ckpt = str(ckpt_name_splits[0]) + '.' + str(ckpt_name_splits[1])\n",
    "                ckpt_path = os.path.join(snapshot_dir, ckpt)\n",
    "                if os.path.exists(ckpt_path + '.index') and os.path.exists(ckpt_path + '.meta') and \\\n",
    "                        os.path.exists(ckpt_path + '.data-00000-of-00001'):\n",
    "                    is_valid = True\n",
    "\n",
    "            return is_valid, ckpt\n",
    "\n",
    "        def scan_psnr_folder():\n",
    "            tested_ckpt_in_psnr_sets = set()\n",
    "            for test_psnr in os.listdir(psnr_dir):\n",
    "                tested_ckpt_in_psnr_sets.add(test_psnr)\n",
    "            return tested_ckpt_in_psnr_sets\n",
    "\n",
    "        def scan_model_folder():\n",
    "            saved_models = set()\n",
    "            for ckpt_name in os.listdir(snapshot_dir):\n",
    "                is_valid, ckpt = check_ckpt_valid(ckpt_name)\n",
    "                if is_valid:\n",
    "                    saved_models.add(ckpt)\n",
    "            return saved_models\n",
    "\n",
    "        tested_ckpt_sets = scan_psnr_folder()\n",
    "        while True:\n",
    "            all_model_ckpts = scan_model_folder()\n",
    "            new_model_ckpts = all_model_ckpts - tested_ckpt_sets\n",
    "            if len(new_model_ckpts) == 0:\n",
    "                break\n",
    "            for ckpt_name in new_model_ckpts:\n",
    "                # inference\n",
    "                ckpt = os.path.join(snapshot_dir, ckpt_name)\n",
    "                inference_func(ckpt, dataset_name, evaluate_name)\n",
    "\n",
    "                tested_ckpt_sets.add(ckpt_name)\n",
    "\n",
    "            print('waiting for models...')\n",
    "            evaluate.evaluate('compute_auc', psnr_dir)\n",
    "            time.sleep(60)\n",
    "    else:\n",
    "        inference_func(snapshot_dir, dataset_name, evaluate_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize prediction module output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from checkpoints/taiwan_sa_l_2_alpha_1_lp_1.0_adv_0.05_gdl_1.0_flow_2.0/model.ckpt-1000\n",
      "Restored model parameters from checkpoints/taiwan_sa_l_2_alpha_1_lp_1.0_adv_0.05_gdl_1.0_flow_2.0/model.ckpt-1000\n"
     ]
    }
   ],
   "source": [
    "ckpt_name = 'model.ckpt-1000'\n",
    "ckpt = os.path.join(snapshot_dir, ckpt_name)\n",
    "video_name = '000489'\n",
    "i = 50\n",
    "with tf.Session(config=config) as sess:\n",
    "    load(loader, sess, ckpt)\n",
    "    video_clip = data_loader.get_video_clips(video_name, i - num_his, i + 1) # video clip size is (W,H,(4+1)*3)\n",
    "    pred_frame = sess.run(test_outputs,\n",
    "                        feed_dict={test_video_clips_tensor: video_clip[np.newaxis, ...]})\n",
    "    gt_frame = video_clip[:,:,-3:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n",
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fd29c0deba8>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(figsize=(16, 8), nrows=2, ncols=1)\n",
    "ax1.imshow(pred_frame[0])\n",
    "ax2.imshow(gt_frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.imshow(video_clip[:,:,:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
